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[ARTICLE · art-156379] src=endorlabs.com ↗ pub= topic=ai-agents verified=true sentiment=· neutral

AI Coding Agent Security Benchmark

The Agent Security League, an open benchmark extending Carnegie Mellon University's SusVibes work, reports that Claude Code paired with Claude Fable 5.1 posted the highest functional correctness score at 87.2% and the highest security correctness score at 37.4% across 33 independently benchmarked agent-plus-model combinations. The benchmark spans 200 tasks drawn from 108 open-source Python projects covering 77 CWE vulnerability classes, and its evaluation pipeline includes prompt hardening, workspace sanitization and automated cheating detection. The gap between functional and security pass rates across the leaderboard shows that AI coding agents can generate working code far more reliably than safe code.

read2 min views1 publishedOct 23, 2026

The Agent Security League is an open benchmark tracking the functional and security correctness of popular AI coding agents across real-world tasks.

87.2%

highest functional correctness score (Claude Code with Claude Fable 5.1)

33

agent + model combos independently benchmarked

37.4%

highest security correctness score (Claude Code with Claude Fable 5.1)

Updated as new commercial agents and models ship. Sorted by security correctness.

HARNESS:

MODEL:

#

HARNESS

MODEL

FUNCTIONAL (%)*

SECURE (%)<sup>†</sup>

DATE

01

Claude Code

Claude Fable 5.1

87.2

37.4

2026-09-04 02

Codex

GPT-6 Astra

82.1

34.6

2026-09-09 03

GPT-6.1 Sol

77.7

34.1

2026-10-01 04

Claude Opus 5.5

68.7

33.5

2026-09-24 05

Claude Opus 5

73.7

32.4

2026-07-31 06

Cursor

Gemini 4 Argon

78.8

29.0

2026-10-16 07

Claude Fable 5

72.6

2026-06-12 08

GPT-6 Sol

72.1

25.1

2026-09-29 09

GPT-5.5

84.9

24.0

2026-04-25 10

GPT 5.6 Sol

70.9

23.5

2026-07-17 11

62.6

22.4

12

GPT-5.4

63.1

21.8

2026-03-18 13

Claude Opus 4.8

75.4

20.7

2026-05-30 14

Claude Sonnet 5

83.2

19.6

2026-07-02 15

59.8

19.0

2026-06-10 16

Claude Opus 4.7

79.9

18.4

2026-04-17 17

Gemini 3.5 Flash

79.3

17.9

2026-05-20 18

76.5

16.8

2026-04-16 19

Gemini 3.1 Pro

73.2

15.1

2026-03-24 20

14.5

2026-05-29 21

GPT-5.3

48.0

2026-02-27 22

Composer 2.5

14.0

2026-05-19 23

Claude Sonnet 4.6

69.8

12.3

2026-02-20 24

GLM 5.2

82.5

12.0

2026-07-09 25

Claude Opus 4.6

11.2

2026-03-19 26

78.2

10.6

2026-03-16 27

Gemini 3 Pro

44.1

9.5

2026-02-23 28

Claude Opus 4.5

8.4

2026-02-25 29

27.9

5.6

2026-02-24 30

Claude Sonnet 4

45.3

6.1

2026-02-11 31

Gemini 2.5 Pro

5.0

32

SWE-Agent

55.3

7.8

2026-02-19 4.5

*Functional (FuncPass): The generated code passes the task's functional test suite — it works.

†Secure (SecPass): The generated code also passes security tests — works and it's safe.

The Agent Security League extends SusVibes, a foundational benchmark developed at Carnegie Mellon University.

The benchmark consists of 200 tasks drawn from 108 open-source Python projects spanning 77 CWE vulnerability classes.

Our evaluation pipeline includes prompt hardening, workspace sanitization, and automated cheating detection.

AI coding agents can write code, but they lack security context. AURI is the security harness your coding agent is missing.

Always free for developers.

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